We use large language models to identify canons of statutory interpretation over the entire life of the Supreme Court, in order to discover previously unknown canons, track canon use at the court, and identify the conditions under which canons are applied. The paper makes methodological contributions to the study of large legal datasets as well as substantive contributions to the field of statutory interpretation.

About the Speaker

Jonathan H. Choi is a professor of law at USC Gould School of Law. He specializes in law and artificial intelligence (applying natural language processing to study legal issues), tax law and statutory interpretation. His work has appeared in the New York University Law Review, the Stanford Law Review, the Yale Journal on Regulation and the Yale Law Journal, among others. His work has been covered by a wide variety of news outlets, including ABC News, Bloomberg, CBS News, CNN, the Daily Mail, Fox News, NBC Nightly News, the New Yorker, Reuters, the Star Tribune, and the Washington Post.

Choi graduated summa cum laude from Dartmouth College, with a triple major in computer science, economics and philosophy and earned high honors for his computer science thesis. He earned a JD at the Yale Law School, where he was the executive bluebook editor of the Yale Law Journal and a founding co-director of the Yale Journal on Regulation Online. Before entering academia, he practiced tax law at Wachtell, Lipton, Rosen & Katz in New York. He previously taught at the University of Minnesota Law School.